...We focused on the top 10 global crops that provide the bulk of consumable food calories: Maize (corn), rice, wheat, soybeans, oil palm, sugarcane, barley, rapeseed (canola), cassava and sorghum. Roughly 83 percent of consumable food calories come from just these 10 sources. Other than cassava and oil palm, all are important U.S. crops.

We found that climate change has affected yields in many places. Not all of the changes are negative: Some crop yields have increased in some locations. Overall, however, climate change is reducing global production of staples such as rice and wheat. And when we translated crop yields into consumable calories – the actual food on people’s plates – we found that climate change is already shrinking food supplies, particularly in food-insecure developing countries. ...

...we estimated that climate change was reducing global rice yields by 0.3% and wheat yields by 0.9% on average each year.

In contrast, some more drought-tolerant crops have benefited from climate change. Yields of sorghum, which many people in the developing world use as a food grain, have increased by 0.7% in sub-Saharan Africa and 0.9% yearly in western, southern and southeastern Asia due to climate shifts since the 1970s. ...

In the United States corn and soybeans are important cash crops, with a combined value of more than US$90 billion in 2017. We found that climate change is causing a small net increase in yields of these crops – on average, about 0.1% and 3.7% respectively each year.

But these numbers reflect both gains and losses. In some Corn Belt states, such as Indiana and Illinois, climate change is shaving up to 8% off of annual corn yields. At the same time, it has boosted annual yields in Iowa and Minnesota by approximately 2.8%. ...

Crop yields are projected to decrease under future climate conditions, and recent research suggests that yields have already been impacted. However, current impacts on a diversity of crops subnationally and implications for food security remains unclear. Here, we constructed linear regression relationships using weather and reported crop data to assess the potential impact of observed climate change on the yields of the top ten global crops–barley, cassava, maize, oil palm, rapeseed, rice, sorghum, soybean, sugarcane and wheat at ~20,000 political units. We find that the impact of global climate change on yields of different crops from climate trends ranged from -13.4% (oil palm) to 3.5% (soybean). Our results show that impacts are mostly negative in Europe, Southern Africa and Australia but generally positive in Latin America. Impacts in Asia and Northern and Central America are mixed. This has likely led to ~1% average reduction (-3.5 X 1013 kcal/year) in consumable food calories in these ten crops. In nearly half of food insecure countries, estimated caloric availability decreased. Our results suggest that climate change has already affected global food production.

Note that this research is based on observed climate change over the past 45 years, and has nothing to do with forecasts of future climate change.

Once we had constructed an empirical model connecting crop yield to weather variations at each location, we could use it to assess how much yields had changed from what we would have expected to see if average weather patterns had not changed. The difference between what we would have predicted, based on the counterfactual weather, and what actually occurred reflects the influence of climate change.

PLoS One, 5/31/19: Climate change has likely already affected global food production...But these numbers reflect both gains and losses. In some Corn Belt states, such as Indiana and Illinois, climate change is shaving up to 8% off of annual corn yields...Note that this research is based on observed climate change over the past 45 years, and has nothing to do with forecasts of future climate change.

So according to their estimates the approximately 250% increase in corn yield we have witnessed over 45 years could have been 258% according to their non-validated models. LOL.

The link didn't hold the actual report and didn't show the statistical methods used. As usual there are a ton of lurking variables. Justa couple examples could be from many farmers switching from high yield feed corn to lower yield sweet corn (my grandparents did this) or even going to a super high quality organic. Or the farmers might be dealing with consumer sentiment over corn syrup and switching to a more profitable crop (not measured in this study).

It's a fair question to also ask what has happened to oats, amaranth (basically didn't exist in the 70s as a consumer good), potatoes (of many varietals), or other such new and niche products that have a health quality corn, rice, and wheat don't have. Wonder Bread briefly went out of business after all.

It would be easier to believe if the grocery store of the past is the grocery store of the present. But without core data or interviewing the researchers it's hard to draw a conclusion.

The link didn't hold the actual report and didn't show the statistical methods used.

The second link I posted is for the actual report, which includes the statistical methods in the "Methods" section. The math is beyond me.

Their goal was to separate out the crop yield changes that were due to rainfall and temperature changes. I assume the researchers are aware of changes in consumer sentiment etc that might affect the data. Whether they have successfully separated out only the climate-related changes, I am not qualified to say. Use your own judgment and adjust your prepping plans accordingly.

I should have put a better title on this thread -- e.g., Increase in global food production since 1974 is estimated to be 1% less than it would have been, due to climate change -- but there's a limit of how many characters you can fit into a title.

"Future studies should explore spatial and temporal multi-scale effects [50]; we do not consider potential physical interaction between the explanatory variables at different scales in different geographical units. We would also like to caveat against interpreting our regression-based analysis as causality. Needless to say, detailed studies using technically more complex statistical models, including causal models, and more extensive model diagnostics, is needed. Ignoring spatial autocorrelation does not necessarily bias the final results, however inclusion of such effects may improve the precision of the estimates. On the other hand, spatio-temporal statistical models can be computationally and mathematically very challenging. Future publications should try to address spatio-temporal dependency, diagnostics associated with statistical modeling and other issues mentioned above in global-scale studies."

Several parts of the methodology section cautioned that very simple regressioon models were used and many assumptions made. In a nutshell they concluded that there likely is a correlation between changes in food production and localized climates (claiming to study a few global crops is actually a series of localized studies).

And I'll add the first posted article was written by a politics writer so take it worth a grain of salt. She likely can't parse a scientific paper anyway. But it's good research with a VERY misleading title. I'm surprised it was accepted as titled. Without the causality (which they caution us not to glean) it's really an effective study on how a localized climate could effect crops which is very valuable to the farming community.